MyLab Math with Pearson eText -- Combo Access Card -- for Finite Mathematics and Calculus with Applications (24 months)

by Margaret Lial / Raymond Greenwell

• ISBN13: 9780137419302
• ISBN10: 0137419309
• Edition: 11th
• Format: Access Card
• Copyright: 2021-04-08
• Publisher: PEARSON

Summary

This MyLab^® Combo Access pack includes a MyLab Math access code plus a loose-leaf print version (delivered by mail) to complement your MyLab experience. 

For freshman/sophomore, 2-semester or 2-3 quarter courses covering finite mathematics and applied calculus for students in business, economics, social sciences, or life sciences.

This ISBN is for the 24-month MyLab  Combo Access pack. Pearson eText is included. 

An applied presentation that makes the math meaningful 

Finite Mathematics and Calculus with Applications,?11th Edition?prepares you for success in your future career with timely applications incorporated throughout. Known for using real data in their examples and exercises, the authors make mathematics relevant and accessible throughout the narrative, examples, exercise sets, and supplementary resources. You’ll have ample opportunity to relate what you’re learning to career situations through the Apply It question at the beginning of sections, the applied examples and exercises, and the Extended Application at the end of each chapter. The 11th Edition introduces coauthor Geoffrey Krader, whose enhancements to the MyLab^® Math course make it an even more valuable learning resource. 

Personalize learning with MyLab Math with Pearson eText 

This flexible digital platform combines unrivaled content, online assessments, and customizable features so you can personalize learning and improve results.

Pearson eText is an easy-to-use digital textbook available within MyLab that lets you read, highlight, and take notes all in one place. 

NOTE: Before purchasing, check with your instructor to confirm the correct ISBN. Several versions of the MyLab^® and Mastering^® platforms exist for each title, and registrations are not transferable. To register for and use MyLab or Mastering, you may also need a Course ID, which your instructor will provide. 

Used books, rentals, and purchases made outside of Pearson 

If purchasing or renting from companies other than Pearson, the access codes for the MyLab platform may not be included, may be incorrect, or may be previously redeemed. Check with the seller before completing your purchase. 

Author Biography

Marge Lial ?(late) was always interested in math; it was her favorite subject in the first grade! Marge's intense desire to educate both her students and herself has inspired the writing of numerous best-selling textbooks. Marge, who received bachelor's and master's degrees from California State University at Sacramento, was affiliated with American River College. An avid reader and traveler, her travel experiences often found their way into her books as applications, exercise sets, and feature sets. Her interest in archeology led to trips to various digs and ruin sites, producing some fascinating problems for her textbooks involving such topics as the building of Mayan pyramids and the acoustics of ancient ball courts in the Yucatan.

Raymond N. Greenwell ?earned a B.A. in Mathematics and Physics from the University of San Diego, and an M.S. in Statistics, an M.S. in Applied Mathematics, and a Ph.D. in Applied Mathematics from Michigan State University, where he earned the graduate student teaching award in 1979. After teaching at Albion College in Michigan for four years, he moved to Hofstra University in 1983, where he currently is Professor of Mathematics.

Raymond has published articles on fluid mechanics, mathematical biology, genetic algorithms, combinatorics, statistics, and undergraduate mathematics education. He is a member of MAA, AMS, SIAM, NCTM, and AMATYC. He has served as governor of the Metropolitan New York Section of the MAA, as well as webmaster and liaison coordinator, and he received a distinguished service award from the Section in 2003. He is an outdoor enthusiast and leads trips in the Sierra Club's Inner City Outings program.

Nathan P. Ritchey ?earned a B.A. in Mathematics with a minor in Music from Mansfield University of Pennsylvania. He earned a M.S. in Applied Mathematics and a Ph.D. in Mathematics from Carnegie Mellon University. He is former chair of the Department of Mathematics and Statistics at Youngstown State University and is currently serving as the dean of the College of Science and Health Professions at Edinboro University. He has published articles in economics, honors education, medicine, mathematics, operations research, and student recruitment. Nate is a Consultant/Evaluator for the North Central Association's Higher Learning Commission and regularly participates in program evaluations.

In recognition of his numerous activities, Nate has received the Distinguished Professor Award for University Service, the Youngstown Vindicator's "People Who Make a Difference Award," the Watson Merit Award for Department Chairs, the Spirit in Education Award from the SunTex corporation, and the Provost's Merit Award for significant contributions to the Honors Program.

Katherine Ritchey earned a B.A. in Mathematics from the University of Notre Dame. She earned a Ph.D. in Mathematics from The Ohio State University, and her research interests include combinatorics and graph theory. While at OSU, she began her lifelong dream of teaching mathematics and was awarded several graduate student teaching awards. She is currently an Assistant Professor of Mathematics at the University of Mount Union in Ohio.

Blain A. Patterson earned a BS in Mathematics Education with a minor in Mathematics from Youngstown State University. He earned both a MS and PhD in Mathematics Education from North Carolina State University. He is currently an Assistant Professor of Applied Mathematics at Virginia Military Institute. He has published articles in various mathematics and education journals on mathematics teacher education, learning disabilities, middle school mathematics education, and cryptography. Blain is currently a Project NExT Fellow (Brown '20) and an active member of MAA, SIAM, SIMIODE, and AWM. When he is not thinking about mathematics, Blain enjoys spending time outdoors with his dogs and playing board games.

Sarah Ritchey Patterson earned a B.S. in Mathematics and Computer Science from Youngstown State University. She earned a Ph.D. in Mathematics from Duke University. Sarah is currently an assistant professor at the Virginia Military Institute. Her research interests include computational fluid dynamics, fluid-structure interaction problems, and mathematical modeling. Sarah actively advises undergraduate research projects and uses this perspective to enhance her teaching and the textbook.

Geoffrey H. Krader received a B.S. in Mathematics from the University of Michigan and a M.A in Mathematics from the University of Wisconsin-Madison. After college, Geoff began a career in private industry, where he directed large, global software development teams at Bell Laboratories and Lucent Technologies. He retired after 25 years to begin a second career in teaching, something he had enjoyed since graduate school where he was a teaching assistant. For 15 years, Geoff was a full-time faculty member in the mathematics department at Morton College, just outside of Chicago. At Morton, he led a redesign of the developmental mathematics curriculum that improved student outcomes, and he used his business experience to bring real-life examples into the courses he taught. Geoff is also an avid traveler and photographer. He has visited all 50 U.S. states and almost 30 foreign countries on four continents.

Table of Contents

Preface
Prerequisite Skills Diagnostic Test

R. Algebra Reference
R.1 Polynomials
R.2 Factoring
R.3 Rational Expressions
R.4 Equations
R.5 Inequalities
R.6 Exponents
R.7 Radicals

1. Linear Functions
1.1 Slopes and Equations of Lines
1.2 Linear Functions and Applications
1.3 The Least Squares Line
Chapter 1 Review
Extended Application: Predicting Life Expectancy

2. Systems of Linear Equations and Matrices
2.1 Solution of Linear Systems by the Echelon Method
2.2 Solution of Linear Systems by the Gauss-Jordan Method
2.3 Addition and Subtraction of Matrices
2.4 Multiplication of Matrices
2.5 Matrix Inverses
2.6 Input-Output Models
Chapter 2 Review
Extended Application: Contagion

3. Linear Programming: The Graphical Method
3.1 Graphing Linear Inequalities
3.2 Solving Linear Programming Problems Graphically
3.3 Applications of Linear Programming
Chapter 3 Review
Extended Application: Sensitivity Analysis

4. Linear Programming: The Simplex Method
4.1 Slack Variables and the Pivot
4.2 Maximization Problems
4.3 Minimization Problems; Duality
4.4 Nonstandard Problems
Chapter 4 Review
Extended Application: Using Integer Programming in the Stock-Cutting
Problem

5. Mathematics of Finance
5.1 Simple and Compound Interest
5.2 Future Value of an Annuity
5.3 Present Value of an Annuity; Amortization
Chapter 5 Review
Extended Application: Time, Money, and Polynomials

6. Logic
6.1 Statements
6.2 Truth Tables and Equivalent Statements
6.3 The Conditional and Circuits
6.4 More on the Conditional
6.5 Analyzing Arguments and Proofs
6.6 Analyzing Arguments with Quantifiers
Chapter 6 Review
Extended Application: Logic Puzzles

7. Sets and Probability
7.1 Sets
7.2 Applications of Venn Diagrams
7.3 Introduction to Probability
7.4 Basic Concepts of Probability
7.5 Conditional Probability; Independent Events
7.6 Bayes' Theorem
Chapter 7 Review
Extended Application: Medical Diagnosis

8. Counting Principles; Further Probability Topics
8.1 The Multiplication Principle; Permutations
8.2 Combinations
8.3 Probability Applications of Counting Principles
8.4 Binomial Probability
8.5 Probability Distributions; Expected Value
Chapter 8 Review
Extended Application: Optimal Inventory for a Service Truck

9. Statistics
9.1 Frequency Distributions; Measures of Central Tendency
9.2 Measures of Variation
9.3 The Normal Distribution
9.4 Normal Approximation to the Binomial Distribution
Chapter 9 Review
Extended Application Statistics in the Law--the Castaneda Decision

10. Nonlinear Functions
10.1 Properties of Functions
10.2 Quadratic Functions; Translation and Reflection
10.3 Polynomial and Rational Functions
10.4 Exponential Functions
10.5 Logarithmic Functions
10.6 Applications: Growth and Decay; Mathematics of Finance
Chapter 10 Review
Extended Application: Power Functions

11. The Derivative
11.1 Limits
11.2 Continuity
11.3 Rates of Change
11.4 Definition of the Derivative
11.5 Graphical Differentiation
Chapter 11 Review
Extended Application: A Model for Drugs Administered Intravenously

12. Calculating the Derivative
12.1 Techniques for Finding Derivatives
12.2 Derivatives of Products and Quotients
12.3 The Chain Rule
12.4 Derivatives of Exponential Functions
12.5 Derivatives of Logarithmic Functions
Chapter 12 Review
Extended Application: Electric Potential and Electric Field

13. Graphs and the Derivative
13.1 Increasing and Decreasing Functions
13.2 Relative Extrema
13.3 Higher Derivatives, Concavity, and the Second Derivative Test
13.4 Curve Sketching
Chapter 13 Review
Extended Application: A Drug Concentration Model for Orally Administered Medications

14. Applications of the Derivative
14.1 Absolute Extrema
14.2 Applications of Extrema
14.3 Further Business Applications
14.4 Implicit Differentiation
14.5 Related Rates
14.6 Differentials: Linear Approximation
Chapter 14 Review
Extended Application: A Total Model for a Training Program

15. Integration
15.1 Antiderivatives
15.2 Substitution
15.3 Area and the Definite Integral
15.4 The Fundamental Theorem of Calculus
15.5 The Area Between Two Curves
15.6 Numerical Integration
Chapter 15 Review
Extended Application Estimating Depletion Dates for Minerals

16. Further Techniques and Applications of Integration
16.1 Integration by Parts
16.2 Volume and Average Value
16.3 Continuous Money Flow
16.4 Improper Integrals
16.5 Solutions of Elementary and Separable Differential Equations
Chapter 16 Review
Extended Application: Estimating Learning Curves in Manufacturing With Integrals

17. Multivariable Calculus
17.1 Functions of Several Variables
17.2 Partial Derivatives
17.3 Maxima and Minima
17.4 Lagrange Multipliers
17.5 Total Differentials and Approximations
17.6 Double Integrals
Chapter 17 Review
Extended Application: Using Multivariable Fitting to Create a Response Surface Design

18. Probability and Calculus
18.1 Continuous Probability Models
18.2 Expected Value and Variance of Continuous Random Variables
18.3 Special Probability Density Functions
Chapter 18 Review
Extended Application Exponential Waiting Times